Tetra-Nucleotide Histogram-Based Analysis of Metagenomic Data for Investigating Antibiotic-Resistant Bacteria

被引：0

作者：

Klautau, S. P. ^{[1
]}

Pinheiro, S. L. ^{[1
]}

Nascimento, A. M. ^{[1
]}

Castro, P. A. ^{[1
]}

Ramos, R. ^{[2
]}

Klautau, A. ^{[1
]}

机构：

[1] Fed Univ Para UFPA, LASSE Biomed Engn Grp, Belem, Para, Brazil

[2] UFPA, Lab Genom & Bioinformat, Ctr Genom & Biol Sistemas, Belem, Para, Brazil

来源：

XXVII BRAZILIAN CONGRESS ON BIOMEDICAL ENGINEERING, CBEB 2020 | 2022年

关键词：

Signal processing; Metagenomics; Histograms; Bioinformatics; Antibiotic-resistant bacteria;

D O I：

10.1007/978-3-030-70601-2_350

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

In recent years, technology-based studies have surfaced due to the growing interest in the global problem of antibiotic resistance, especially in the bioinformatics field applied to metagenomics, which is able to represent the microorganism and its associated genes in terms of antibiotic resistance. This paper aims to present a novel approach to categorize antibiotic-resistant genes data based on metagenomic databases through an analysis with histogram-based signal processing. The preliminary results show that the approach is effective to identify antibiotic-resistant genes and has a relatively low computational cost.

引用

页码：2379 / 2384

页数：6

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